A signal classifier is a device that analyzes an input signal to determine which of a plurality of signal classes the signal belongs to. Signal classifiers have been used in communications systems to, among other things, classify signals received from a communications channel to determine how to properly process the signals. For example, a receiver needs to know the type of modulation present in a received signal to properly demodulate the signal. A signal classifier can be used to determine the modulation type so that a proper demodulation method can be selected.
In general, all signal classifiers examine signal feature differences to discriminate between signal classes. A cluttered, interference-laden environment tends to reduce the possible resolution between signal classes, resulting in a situation where similar signal classes are difficult to distinguish. For this reason, many prior-art signal classifiers perform poorly in noisy environments. In addition, many prior-art signal classifiers use "signal-specific" procedures and signal processing steps that preclude addition or deletion of signals-of-interest.
Prior-art signal classifiers are also very computationally complex. That is, known classifiers normally require a relatively large amount of computation time in a system processor. As can be appreciated, the computational complexity of these signal classifiers can slow down system operation significantly and may require the use of additional or more powerful (and more expensive) processors. In addition, execution of these complex signal classification methods in a processor generally consumes a relatively large amount of electrical power, making the methods undesirable for use in applications where power is scarce (e.g., satellite and handheld applications).
In addition to the above, prior-art signal classifiers are relatively difficult to train (i.e., to teach the classifier to recognize different signal classes). For example, these signal classifiers generally require retraining or software restructuring for all signal classifications whenever a new signal classification is added to the system. In addition, prior-art signal classifiers typically require complex feature set extraction, are not adaptive to varying modulation types or multiplexing types, and/or are highly sensitive to communication channel effects.
Therefore, a need exists for a method and apparatus for performing discriminative signal classification in a communications system that is reliable, of relatively low complexity, and which provides a high level of discrimination between signal classes. In addition, a need exists for flexible classification methods that provide for the addition of new signal classes or the removal of undesired signal classes without the need for extensive system reconfiguration.